Precipitation Projection Using LARS-WG and CMIP6 Models

Climate change has significantly impacted the environment across various regions worldwide. The growing interest in these impacts has raised the incentive of scholars to investigate and predict variations in critical weather variables, such as precipitation, to supply helpful baseline results for future planning and control. This research attempts to assess the effects of global warming on precipitation in Soran City in northern Iraq. The daily rainfall is downscaled utilizing the LARS-WG (8.0) model with six General Circulation Models (GCMs) and the SSP585 scenario for 2021-2040. These outcomes establish that the statistical analysis confirmed the LARS-WG model's ability and reliability in downscaling precipitation.Additionally, the average rainfall of six GCMs will likely fluctuate during the year. The highest increase is anticipated in January and October, while the most decrease is expected in February, March, and November. The findings can enhance the understanding of the effects of climate change on water availability and motivate managers and stakeholders to develop the most effective techniques for mitigating these impacts.